4:30pm: IT as the Transmission of the Sprint Business Engine by Stefan Stroebel

5:00pm: Machine Learning at Elastic by Morgan Goeller

6:00pm: Wrap-up

IT as the Transmission of the Sprint Business Engine

In this talk, Stefan will share how the IT department at Sprint transformed from beyond ensuring the company has enough hardware and is producing error-free code to helping business units across the company make data-driven decisions.

How?

By ingesting nearly 3 billion records a day, including data from logs, databases, emails, syslogs, test messages, and internal and vendor application APIs, into the Elastic Stack. This 50 TB of real-time data allows their marketing team to monitor the performance and user experience of Sprint.com, their retail operations group to monitor the performance of their demo phones, their wholesale sales unit to understand the hundreds of B2B relationships they maintain, and much, much more.

Stefan Stroebel is using Elastic to lift the vail of IT to the business allowing the massive amount of log data to be used to make vital business decisions. As a technical architect implementing many complex platforms in his 20 year IT career, none has made a faster, greater, broader impact than implementing the Elastic stack. In just under two years, Elk has been implemented to monitor 17,000 servers, 2500 retail stores nationwide and understanding the client journey on the company's web presence. Stefan is regularly called in to troubleshoot complex application performance issues and assist the business in understanding their customers better.

Machine Learning at Elastic

More companies, from startups to large enterprises, are storing large amounts of structured and unstructured data, especially in Elasticsearch. With 'search' becoming the foundation for many of these companies to address their most complex use cases, users need an an automated way to understand the 'why' in their data and take action on 'difficult to see' insights. Machine Learning is the next step to making this happen.

Prelert is a Behavioral Analytics platform that uses Machine Learning to analyze log data, find anomalies within the data, and links them together. We allow your data to tell its story.

Detecting advanced security threat activities and anomalies in log data. Discovering hidden fraud patterns in highly sensitive data. Identifying anomalous systems or metrics and their root causes across IT systems. Linking together complex series of events in data to expose early warning signals. Automatically pinpointing where and why critical system outages are occurring. Detecting unexpected drops in transactional activity, and much more.

In this talk, we will demonstrate how to combine and automate the use of search, and machine learning to get a comprehensive view of all of your data.

Morgan Goeller is a Solutions Architect for Elastic, focusing on real-time analytics and visualization. He has been in the tech industry for the last 20 years, working with customers in Digital Marketing, Telecommunications, Energy, and Healthcare. Morgan has a degree in Mathematics with an emphasis in Scientific Computation and lives in Austin, TX.